PROJECT SUMMARY Developing an Automated Yeast Dissection System for Aging Research Aging is the single greatest risk factor for diseases that are principal causes of mortality. The objectives of aging research are to discover key genes and pathways related to aging that may eventually contribute to retardation of aging and a delay in the onset of age-associated diseases. The budding yeast Saccharomyces cerevisiae has been a powerful model for the study of aging and has enabled significant contributions to our understanding of basic mechanisms of aging in eukaryotic cells. However, traditional assays of yeast aging, including microdissection methods, have technical challenges; for instance, the methods are low-throughput and the experimental procedures are laborious. An experiment typically lasts several weeks or months, and requires overnight storage of the assayed cells at a refrigerator to pause replication throughout the course of experiment. This tedious procedure has substantially hindered progress in the field of aging research. Herein, we propose to develop automated dissection system that enable continuous and automatic dissection of daughter cells without disturbing mother cells as they bud. The system allows an automated whole-lifespan tracking with high spatiotemporal resolution and large-scale quantification of single yeast cells, resulting in significant reduction of labor, time, and cost. In addition, the high-resolution florescence imaging of yeast cells grown in constant and dynamically changing environments offers the ability to examine the dynamics of gene expression and signaling networks in a high-throughput manner. The quantity and types of data acquired by this system are impossible with the traditional assay methods. In Phase I of this STTR grant we developed a proof-of-concept prototype automated dissection chip and demonstrated feasibility of the microfluidics-based yeast dissection technology. In Phase II project, we will complete the development of an automated dissection system through scaling-up production of the automated dissection chip and development of a dedicated software to analyze time-lapse images generated from the automated dissection chip. In addition, we will optimize application procedures, assess data variability and finalize quality control standards for commercialization of the automated dissection system.